In Question Answering, Two Heads Are Better Than One
In Question Answering, Two Heads Are Better Than One
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在回答问题时，两个头脑比一个头脑好
DOI：
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发表时间：
2003
期刊：
影响因子：
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通讯作者：
Abraham Ittycheriah
中科院分区：
文献类型：
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作者：
Jennifer Chu;Krzysztof Czuba;J. Prager;Abraham Ittycheriah
受集成方法在机器学习和自然语言处理的其他领域的成功的启发，我们开发了一种多策略和多源的问答方法，该方法基于组合来自不同的回答代理在多个语料库中搜索答案的结果。应答代理采用根本不同的策略，一个主要利用基于知识的机制，另一个采用统计技术。我们提出了我们的多层次的答案解析算法，结合答案代理在问题，通道，和/或答案水平的结果。实验评估我们的答案解析算法的有效性显示了35.0%的相对改善，我们的基线系统中正确回答的问题的数量，和32.8%的改善，根据平均精度指标。
Motivated by the success of ensemble methods in machine learning and other areas of natural language processing, we developed a multi-strategy and multi-source approach to question answering which is based on combining the results from different answering agents searching for answers in multiple corpora. The answering agents adopt fundamentally different strategies, one utilizing primarily knowledge-based mechanisms and the other adopting statistical techniques. We present our multi-level answer resolution algorithm that combines results from the answering agents at the question, passage, and/or answer levels. Experiments evaluating the effectiveness of our answer resolution algorithm show a 35.0% relative improvement over our baseline system in the number of questions correctly answered, and a 32.8% improvement according to the average precision metric.